{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.dates as mdates\n",
    "from matplotlib.collections import PatchCollection\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_timeline(timeline, label, ypos, ax, width=0.1, hatch=None, fill=True):\n",
    "\n",
    "    tlim = ax.get_xlim()[0]\n",
    "    t0 = tlim - (8.*365.) # text x-position\n",
    "\n",
    "    tbeg = mdates.date2num(dt.datetime.strptime(timeline['start'], '%Y%m%d'))\n",
    "    tend = mdates.date2num(dt.datetime.strptime(timeline['end'], '%Y%m%d'))\n",
    "    tnow = mdates.date2num(dt.datetime.now())\n",
    "    \n",
    "    if tbeg < tlim: tbeg = tlim # Set start of rectangle to lower limit of plot\n",
    "        \n",
    "    y0 = ypos-(width*0.5) # y-position for rectangle\n",
    "        \n",
    "    #if tend > tnow:\n",
    "    #    rect = []\n",
    "    #    length1 = tnow - tbeg\n",
    "    #    rect.append( mpatches.Rectangle([tbeg, y0], length1, width, color=timeline['color']) )\n",
    "    #    length2 = tend - tnow\n",
    "    #    rect.append( mpatches.Rectangle([tnow, y0], length2, width, color=timeline['color']) )\n",
    "    #    p = PatchCollection(rect)\n",
    "    #    ax.add_collection(p)\n",
    "    #else:\n",
    "    #    length = tend - tbeg\n",
    "    #    rect = mpatches.Rectangle([tbeg, y0], length, width, color=timeline['color'])\n",
    "    #    ax.add_patch(rect)\n",
    "    \n",
    "    length = tend - tbeg\n",
    "    rect = mpatches.Rectangle([tbeg, y0], length, width, color=timeline['color'], \n",
    "                              hatch=hatch, fill=fill)\n",
    "    ax.add_patch(rect)\n",
    "    \n",
    "    ax.annotate(label, xy=(tbeg, y0), xytext=(t0, ypos-0.02), fontsize=36)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "stale = 'lightpink'\n",
    "discontinued = '0.5'\n",
    "current = 'red'\n",
    "old = 'khaki'\n",
    "tobediscontinued = 'salmon'\n",
    "reanalysis = {\n",
    "              'ASR':    {'start': '20000101', 'end': '20111231', 'color': stale},\n",
    "              'MERRA':  {'start': '19790101', 'end': '20160229', 'color': discontinued},\n",
    "              'MERRA2': {'start': '19800101', 'end': '20201231',  'color': current},\n",
    "              'ERA40':  {'start': '19580101', 'end': '20011231', 'color': discontinued},\n",
    "              'ERA-Interim': {'start': '19790101', 'end': '20181231', 'color': tobediscontinued},\n",
    "              'ERA5':   {'start': '20000101', 'end': '20251231', 'color': current},\n",
    "              'NCEP1':  {'start': '19480101', 'end': '20201231', 'color': old},\n",
    "              'NCEP2':  {'start': '19790101', 'end': '20201231', 'color': old},\n",
    "              'CFSR':   {'start': '19790101', 'end': '20251231', 'color': current},\n",
    "              'JRA25':  {'start': '19790101', 'end': '20041231', 'color': discontinued},\n",
    "              'JRA55':  {'start': '19580101', 'end': '20251231', 'color': current},\n",
    "             }\n",
    "\n",
    "missions = {'CRYOSAT-2': {'start': '20101022', 'end': '20221231', 'color': 'aqua'},\n",
    "            'ICESAT': {'start': '20030801', 'end': '20091011', 'color': 'lightskyblue'},\n",
    "            'ICESAT-2': {'start': '20181030', 'end': '20281231', 'color': 'cornflowerblue'},\n",
    "            'ICEBRIDGE': {'start': '20090301', 'end': '20181231', 'color': 'mediumslateblue'},\n",
    "            'ERS-1/2': {'start': '19931001', 'end': '20010331', 'color': 'royalblue'}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9559c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(30,20))\n",
    "\n",
    "ax.set_xlim(dt.datetime(1979,1,1),dt.datetime(2028,12,31))\n",
    "ax.set_ylim(0,2)\n",
    "ax.axvline(dt.datetime.now(), lw=2, c='k')\n",
    "\n",
    "ypos = 2\n",
    "for key in reanalysis.keys():\n",
    "    ypos = ypos - 0.1\n",
    "    add_timeline(reanalysis[key], key, ypos, ax, width=0.08)\n",
    "\n",
    "ypos = 0.7\n",
    "for key in missions.keys():\n",
    "    ypos = ypos - 0.1\n",
    "    add_timeline(missions[key], key, ypos, ax, width=0.08)\n",
    "\n",
    "# Add extra reanalysis symbols\n",
    "add_timeline({'start': '19790101', 'end': '19991231', 'color': current}, \n",
    "             '', 2.-0.6, ax, width=0.08, fill=False, hatch='x')\n",
    "\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['bottom'].set_visible(True)\n",
    "ax.spines['left'].set_visible(False)\n",
    "ax.tick_params(top='off', bottom='on', left='off', right='off', \n",
    "               labelleft='off', labelbottom='on', labelsize=40, color='k', width=3, size=5)\n",
    "\n",
    "diri = r'C:\\Users\\apbarret\\Documents\\Presentations\\AGU2018'\n",
    "fig.savefig(os.path.join(diri,'reanalysis_timeline.png'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
